Triple

T14144924
Position Surface form Disambiguated ID Type / Status
Subject Dora di Veny E350520 entity
Predicate mouthOf P1008 FINISHED
Object Dora Baltea E429981 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Dora Baltea | Statement: [Dora di Veny, mouthOf, Dora Baltea]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dora Baltea
Context triple: [Dora di Veny, mouthOf, Dora Baltea]
  • A. Dora Baltea chosen
    Dora Baltea is a major river in northwestern Italy that flows from the Alps through the Aosta Valley and Piedmont before joining the Po River.
  • B. Dora Luz
    Dora Luz was a Mexican singer and actress best known for her musical performances in classic Disney films of the 1940s.
  • C. Bela
    Bela is a supporting character in the 1941 horror film "The Wolf Man," portrayed as a tormented Romani werewolf whose curse sets the story’s tragic events in motion.
  • D. Bela
    Bela is a historic town in Pakistan’s Balochistan province, known as an administrative and commercial center within the Lasbela region.
  • E. Dora
    Dora is a central character in the Italian film "Life Is Beautiful," portrayed as a loving and courageous mother whose devotion to her family anchors the story’s emotional core.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d827865f608190b311820428ae027b completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61214de081909a5186ff11336f97 completed April 14, 2026, 3:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdf1b8508819096d4f5cf1456edca completed May 7, 2026, 6:51 p.m.
Created at: April 10, 2026, 12:53 a.m.